Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases (eng)

The contributions by epidemic modeling experts describe how mathematical models and statistical forecasting are created to capture the most important aspects of an emerging epidemic.Readers will discover a broad range of approaches to address questions, such as

• Can we control Ebola via ring vaccination strategies?
  
• How quickly should we detect Ebola cases to ensure epidemic control?
  
•  What is the likelihood that an Ebola epidemic in West Africa leads to secondary outbreaks in other parts of the world?  
• When does it matter to incorporate the role of disease-induced mortality on epidemic models?
•  What is the role of behavior changes on Ebola dynamics? 
• How can we better understand the control of cholera or Ebola using optimal control theory?
• How should a population be structured in order to mimic the transmission dynamics of diseases such as chlamydia, Ebola, or cholera?
• How can weobjectively determine the end of an epidemic?
• How can we use metapopulation models to understand the role of movement restrictions and migration patterns on the spread of infectious diseases?
  
• How can we capture the impact of household transmission using compartmental epidemic models?
  
• How could behavior-dependent vaccination affect the dynamical outcomes of epidemic models? 
  

The derivation and analysis of the mathematical models addressing these questions provides a wide-ranging overview of the new approaches being created to better forecast and mitigate emerging epidemics. 

This book will be of interest to researchers in the field of mathematical epidemiology, as well as public health workers.

Gerardo Chowell is an associate professor and a Second Century Initiative Scholar (2CI) in the School of Public Health at Georgia State University in Atlanta. His research program includes the development and application of quantitative approaches for understanding the transmission dynamics and control of infectious diseases including influenza, Ebola, and dengue fever. His work has appeared in high-impact journals including The New England Journal of Medicine, PLOS Medicine, and BMC Medicine, and has been cited by major media outlets including the Washington Post and TIME magazine.

James (Mac) Hyman has developed and analyzed mathematical models for the transmission of HIV/AIDs, influenza, malaria, dengue fever, chikungunya, and infections.  His current focus is to identify approaches where these models can help public health workers be more effective in mitigating the impact of emerging diseases.  He was aresearch scientist at Los Alamos National Laboratory for over thirty years, is a past president of the Society for Industrial and Applied Mathematics (SIAM),  and now holds the Phillips Distinguished Chair in Mathematics at Tulane University.